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Background: Although Lesotho has one of the highest childhood mortality levels in Southern Africa, there has been limited research on the link between type of birth attendant and neonatal mortality in Lesotho. This study examined the relationship between type of birth attendant and neonatal mortality while controlling for socio-demographic characteristics of mothers in Lesotho Methods: The study used data from the children’s file of 2014 Lesotho Demographic and Health Survey data. Kaplan-Meier method was used to estimate neonatal mortality rate and Cox proportional hazard regression model was used to assess the association between type of birth attendant and neonatal mortality. Results: Result shows that 5.3% of all births attended to by non-SBAs resulted into neonatal mortality compared to 2.8% of those attended to by SBA. Result further shows that regardless of socio-demographic characteristics, the risks of neonatal mortality were significantly higher with non-SBAs compared to SBA in Lesotho (HR: 2.00, CI: 1.31-3.06). Conclusion: The risk of neonatal mortality is two times higher among children delivered by Non-SBA. Scale-up in access and uptake of SBA is recommended in Lesotho. Thus, Policy on scale-up access to SBA at delivery at no costs need to be put in place.
This study used a cross-sectional data, which was drawn from the children recode file of the 2014 Lesotho Demographic and Health Survey (LDHS). The LDHS was implemented by the Lesotho Ministry of Health (MOH), while technical assistance was provided by Inner City Fund (ICF) Macro through the MEASURE DHS program, a USAID-funded project. The sample for the 2014 LDHS was selected from a list of enumeration areas using the 2006 Lesotho Population and Housing Census (PHC) which was provided by the Lesotho Bureau of Statistics (BOS). Using probability proportional to size (PPS), 400 clusters of Enumeration Areas (EA) were drawn from the census sample frame, comprising of 118 and 282 clusters from urban and rural areas respectively. The LDHS’s children recode file contains information related to the child’s pregnancy and birth, postnatal care and immunization and health of children of women born in the last five years preceding the survey. The data for the mother of each child is also included. This is because, children’s information was collected from women aged 15–49 years (i.e. information about children were included in the woman’s questionnaire). Information such as, sex of the child, month and year of birth of the child, child’s survival status, age of child and age at death of child if the child had died among others. This research made used of DHS dataset, which is publicly available; however, mailed consent was provided to the authors as per DHS protocol. Detailed information regarding procedures and questionnaires are reported elsewhere http://www.dhsprogram.com/ The outcome variable for the study is neonatal mortality which is measured as the death of a child during the first 28 days of life. The question of whether a child was dead or alive was answered by mothers in the survey. The child’s survival status and the age at death in days are combined to generate the outcome variable and make it amenable to survival analysis. Specifically, children known to have died in the first 28 days of their lives are our interest in this study and are regarded as the event, while children who are still alive after 28 days at the time of the survey are treated as censored observations. The study population is made up of infants born to mothers who had live birth within five years preceding the survey. The explanatory variable of interest in this study is birth attendant type which is dichotomized into SBA and non-SBA. SBA includes doctors, nurses and midwives, while non-SBA includes, traditional healers, relatives or friends, others, and by self. The socio-demographic variables we controlled for in the present study are variables that have been found to be associated with neonatal mortality from existing literatures 7. These control variables include maternal age (categorized as less than 25 years, 25–34 years and 35–49 years), maternal place of residence (categorized as urban and rural), maternal education (categorized as no education & primary education, and secondary & higher education), marital status (categorized as ever married and never married), and maternal wealth index (categorized as poor, middle and rich as opposed to the original measurement of poorest, poorer, middle, richer and richest from the DHS). At the univariate level of analysis, a descriptive statistic using percentage distribution are used to describe the levels of neonatal mortality in Lesotho as well as all the predictor variables as reported by mothers. We also used the Kaplan-Meier curve to estimate neonatal mortality rate. For the multivariate analysis, the Cox proportional regression model was used to examine the effect of birth attendant type on neonatal death while controlling for the mother’s socio-demographic variables. The assumption of the model is that the hazard ratio is constant over time and only covariates (such as education of mother, place of residence, and age of mother, marital status, occupation, and wealth index) that satisfy the assumption of the model are used. Stata 14 was used to analyzed the data and results are interpreted by using Hazard Ratio (HR) with level of significance set at p<0.05 and confidence intervals (CI) of 95%. The Cox model is written as: h(t) = h0 (t) × exp{b1x1 + b2x2 +…+ bpxp} Where the hazard function h(t) is the dependent variable, which is dependent on a set of p covariate (x1,x2,…, xp whose impact is measured by the size of the respective coefficients. (b1, b2,…, bp. The term h0 is the baseline hazard, which gives the value of the hazard if all the xi are equal to zero.
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